The structural shortage list
The roles that got materially harder in the last year include: AI engineers and applied ML engineers, AI product managers, MLOps and AI infrastructure engineers, senior backend engineers with payments or security depth, AI evaluation engineers, AI security and risk specialists, AI legal counsel, AI-aware analytics engineers, agent integration developers, and clinical or domain-AI hybrid roles.
The pattern is the same across the list. Each role requires real production AI experience that was not commonly available five years ago. The supply pool has grown, but demand has grown faster.
Why compensation alone does not close them
Most India hiring teams default to raising salary when a role gets hard. For these roles, that helps but does not solve. Strong AI candidates have multiple offers. They optimize for speed of process, signal quality of the interview, and the team they will actually build with.
A team with a slow loop and a vague evaluation rubric will lose AI candidates even when its compensation is competitive. A team with a fast, structured process can win without paying the very top of the market.
What HR leaders should change
Compress the loop. From application to offer in 14 to 21 days. Replace generic first rounds with structured AI interviews so candidates get a fair, fast experience. Move the panel to a shared workspace so feedback does not stall in side threads. Sell the team and the work, not the perks.
AI talent moves fast. Hiring teams that move slow lose by default.